[GitHub] twdsilva commented on a change in pull request #23400: [SPARK-26499] [SQL] JdbcUtils.getCatalystType maps TINYINT to IntegerType instead of Byte…

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twdsilva commented on a change in pull request #23400: [SPARK-26499] [SQL] JdbcUtils.getCatalystType maps TINYINT to IntegerType instead of Byte…
URL: https://github.com/apache/spark/pull/23400#discussion_r244523235
 
 

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 File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
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 @@ -239,7 +239,7 @@ object JdbcUtils extends Logging {
       case java.sql.Types.TIMESTAMP     => TimestampType
       case java.sql.Types.TIMESTAMP_WITH_TIMEZONE
                                         => null
-      case java.sql.Types.TINYINT       => IntegerType
+      case java.sql.Types.TINYINT       => ByteType
 
 Review comment:
   @HyukjinKwon  Thank you for reviewing.
   
   The range of ```TINYINT``` varies by database. It ranges from -128 to 127 for MySQL(https://dev.mysql.com/doc/refman/8.0/en/integer-types.html), H2 (http://www.h2database.com/html/datatypes.html#tinyint_type) and Phoenix (https://phoenix.apache.org/language/datatypes.html#tinyint_type).
   It ranges from 0 to 255 for SQL Server (https://docs.microsoft.com/en-us/sql/t-sql/data-types/int-bigint-smallint-and-tinyint-transact-sql?view=sql-server-2017)
   
   I think users can implement ```JdbcDialect``` to override the default JDBC to catalyst type mapping when using the JDBC DataSource. Let me know what you think. 
   
   
   

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